Gender Differences in Mathematics, Science, Reading, and Civic Education: An Updated Analysis and Synthesis
Author(s):
Conference:
ECER 2009
Format:
Paper

Session Information

09 SES 06 C, International Large-Scale Assessments: Heterogeneity Issues

Paper Session

Time:
2009-09-29
10:30-12:00
Room:
HG, Elise Richter
Chair:
Renate Schulz-Zander

Contribution

This paper is a very comprehensive assessment of current status of gender differences in multiple learning outcomes including (a) mathematics literacy, (b) science literacy, (c) reading literacy, and (d) civic education, based on the recent data (1997 to 2007) from several regional and international student assessments: 1. Latino Americano Laboratorio de Evaluacion de La Calidad de La Educacion (LAB) (focusing on Latin America) 2. Programme d’Analyse des Systèmes Educatifs des Pays de la CONFEMEN (PASEC) (focusing on Francophone Africa) 3. Southern Africa Consortium for Monitoring Educational Quality (SACMEQ) (focusing on Southern and Eastern Africa) 4. Progress in International Reading Literacy Study (PIRLS) 5. Programme for International Student Assessment (PISA) 6. Third International Mathematics and Science Study (TIMSS). 7. Civic Education Study (CivEd) The overall purpose of this research is to identify where the greatest challenges are in reducing gender differences in education from a global perspective. This goal is achieved by examining gender differences within and between key school subjects. For within school subject analysis of gender differences, the research question deals with whether the degree of gender differences is the same across grade levels, across geographic regions, and between developed and developing countries. For between school subject analysis of gender differences, the research question deals with whether the degree of gender differences is the same across school subjects. A key theoretical framework is adopted as an attempt to understand gender differences in multiple school subjects as unearthed in this research. This theoretical framework comes from school effectiveness that emphasizes schools and teachers as critical factors in understanding gender difference (e.g., King & Hill, 1993; Lloyd, Mensch, & Clark, 2000). Within this theoretical framework are two key elements, school policy and classroom practice, that relate closely with gender differences. This research takes the following positions within these policy and practice elements: (a) access as the centerpiece of school policy (e.g., Finn, 2004; Finn, Gerber, & Wang, 2002) and (b) differential treatment as the centerpiece of classroom practice (e.g., Fennema, Peterson, Carpenter, & Lubinski, 1990; Gambell & Hunter, 2000). Operating in an overarching manner across school policy and classroom practice is gender stereotypes as the broader social factor (e.g., King & Hill, 1993; Swetman, 1995). This theoretical framework provides tentative explanations of gender differences observed in this research.

Method

This research combines data analysis and evidence synthesis techniques. Some large-scale comparative assessments have already analyzed gender differences across grade levels, school subjects, and participating countries. To link these assessments together for the purpose of cross-assessment comparison, a common effect size needs to be calculated. This research relies on standard deviation units as such a common measure to synthesize gender differences across grade levels, school subjects, and participating countries from multiple assessments. For other large-scale comparative studies, gender differences have not been examined as an unique educational issue. For these studies, data analysis is performed to quantify gender differences across grade levels, school subjects, and participating countries. Multiple regression correlation (MRC) techniques are used to quantify gender differences (Cohen & Cohen, 1983). In some cases where large-scale assessments contain both student and school sample weights, hierarchical linear modeling (HLM) techniques are used to quantify gender differences (Raudenbush & Bryk, 2002).

Expected Outcomes

Four major themes have emerged to help identify the greatest challenges in reducing gender differences in education facing the global community. The first theme is that girls have kept their advantage in language across all regional and international student assessments, with the female advantage not only widespread but also substantial. The second theme is that girls are catching up with boys in mathematics achievement with historical female breakthroughs (i.e., first occurrences in history) in this traditionally male domain in both regional and international student assessments. The third theme is that although boys manage to hold on to the male advantage in science, girls have gained ground, with historical female breakthroughs (i.e., first occurrences in history) beginning to take place in this traditionally male domain. The final theme is that there is an overall tendency for boys to achieve higher in civic education in the last year of secondary school.

References

Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis in behavioral sciences. Hillsdale, NJ: Erlbaum. Fennema, E., Peterson, P. L., Carpenter, T. P., & Lubinski, C. A. (1990). Teachers’ attributions and beliefs about girls, boys, and mathematics. Educational Studies in Mathematics, 21, 55-69. Finn, J. D. (2004). Sex differences in educational outcomes: A cross-national study. Sex Roles, 6, 9-26. Finn, J. D., Gerber, S. B., & Wang, M. C. (2002). Course offerings, course requirements, and course taking in mathematics. Journal of Curriculum and Supervision, 17, 336-366. Gambell, T., & Hunter, D. (2000). Surveying gender differences in Canadian school literacy. Journal of Curriculum Studies, 32, 689-719. King, E. M., & Hill, M. A. (Eds.) (1993). Women’s education in developing countries. Baltimore, MD: John Hopkins University Press. Lloyd, C. B., Mensch, B. S., & Clark, W. H. (2000). The effects of primary school quality on school dropout among Kenyan girls and boys. Comparative Education Review, 44, 113-147. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models (2nd ed.). Newbury Park, CA: Sage. Swetman, D. (1995). Rural elementary students’ attitudes toward mathematics. Rural Educator, 16, 20-22.

Author Information

University of Kentucky
Lexington
220

Update Modus of this Database

The current conference programme can be browsed in the conference management system (conftool) and, closer to the conference, in the conference app.
This database will be updated with the conference data after ECER. 

Search the ECER Programme

  • Search for keywords and phrases in "Text Search"
  • Restrict in which part of the abstracts to search in "Where to search"
  • Search for authors and in the respective field.
  • For planning your conference attendance, please use the conference app, which will be issued some weeks before the conference and the conference agenda provided in conftool.
  • If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.